About Me

My Profile Summary

Areas of Expertise 

• NLP: Conversational AI, Large Language Models (LLM's), Code-Mixed Language Models, Emotional Intelligence, Multi-Modal NLP, Core NLP

• Deep Learning, Machine Learning, AI, Generative AI, Explanable AI, Trustable AI 

• Data Science: Spatiotemporal, Multi-step, Multivariate Time Series Forecasting, Cold Start Time Series Forecasting, Knowledge Graphs, Causal Graphs and Causal Learning, Recommendation Systems, Data and Text Analytics.

Experience Details.

1. R&D Technical Team Manager- Fujitsu -India (FRIPL), (APR-2022 to Now). Role: R&D in the area of - Industry Oriented, AI, Core Deep Learning and Graph Neural Networks

   • Role. Managing, Mentoring, Consulting, and Conducting Research work in ‘Causal Graph’, Knowledge Graph, Multi-Variate Time Series Problems.

   • Work Summary & Achievements.

     • Spatiotemporal Multi-Step and Multi-Variate time series forecasting for 5G Network usage. (Paper published at IEEE-Globecom-2023, Patent Filed).

     • Cold-Start Multivariate Time Series Forecasting. (Research paper submitted, Patent Filed).

     • Anomalies Detection in Timeseries Data (Research paper got accepted in ACM WiSec-2024, Patent Filed).

     • Automated Real-Time Storm Chaser System (Research paper submitted, Patent Filed).

     • The Causal Graph Linked Prediction for a large Gene Expression System. (Research paper submitted, Patent Filed).

2. Senior Research Staff and Manager- Samsung Research Institute, Bangalore (India), (May-2020 – to APR-2022). 

   • Role: Managing, Mentoring, Consulting, and Conducting Research work in Conversational AI, NLP, Deep Learning, and Machine Learning.

   • Work Summary & Achievements:

     • The Scalable Multi-Intent System for Company’s conversational AI platform. (Paper published in IEEE Access).

     • Effective Solution for Out-of-domain Intent detection. (Paper published in IEEE Access).

     • Effective Solution for Missing Slot Detection Problem. ( Got US patent - (US 20230077874 A1).

     • AI based Accident Prediction and End-User Support in Smart-Home environment. (Got US Patent - US20230402187A1 )

     • Worked on an Emotional Intelligence supported Conversational AI system.

     • Worked on Age and Gender Prediction problem.

3. Scientist III (Senior Scientist), Computer Science & Eng. at Conduent Labs (Bangalore, India), (Apr-2018 to May-2020)

   • Role: (a) Leadership role, (b) bringing new research projects with strong business alignment, (c) mentoring team members, and (d) conducting high-level R&D works. Achievement (2019-2020)- Got Honor Roll Award from Conduent – For exceeding expectations by demonstrating outstanding attitude and excellent performance.

   • (Research Projects Details):

     • Automatic Crime Volume Prediction System. - (US Patent-US20200410321A1).

     • An Automatic Hate Target Identification System. (US Patent- US20210240938A1)

     • Automated Cyber Hate Profiling System. Achievements - (“Awarded by the Company”).

     • A Code-Mixed Language Model for Aggression Detection (published in COMAD-2020)

     • The adverse drug event detection system (an R&D project). Achievements - Won 1st prize in the Conduent’s 3i HUB (Innovate, Implement and Impact), Initiative.

     •  Quantification of emotion and sentiment. (US Patent US20230325604A1).

     • Automated BOT-Humanization System for Conduent BOT-DARA. Achievements – A Conversational AI Research Project (Patent document Submitted).

4. Senior Machine Learning Scientist, Phenom People (Dec 2016 to Feb-2018)

   • Role: (a) Leadership role, (b) bringing new research projects with strong business alignment, (c) mentoring team members, and (d) conducting high-level R&D works.

   • Research Project details:

     • Developed a novel weighted knowledge graph for (a) Smart B-2-B-2-C hiring, (b) Contextual and (c) Personalized Search.

     • Candidate Social Graph for automatic resource arrangements and supporting business planners and

     • Automatic Job-Highlight System.

5. Post-Doctoral Researcher at University of California (Davis) (Sep-2015 to Sep-2016);

   • “Automatic identification of taxonomy of knowledge from software engineering documents”.

6. Research Professional, TCS Innovation Lab, New Delhi (May 2013 to Aug-2015)  

   • Research Project Details:

     • Automatic Plagiarism Detection system. (winner of the best paper award 1st place @ CICLing-2014)

     • Automatic text-quality grading system (Effectively grades the quality of E-mails, without relevant background model). (Paper published)

     •  Automatic event detection, alignment and prediction system (related to economic events).

7. Research Intern; IBM IRL; Bangalore, India (May 2012 – July 2012) (Research Project details):

   • Developed a new system to answer – “Why based questions” with the help of Wikipedia dump.

Achievements.

1. BEST PAPER AWARD (1st place) @ CICLING-2014 – Details: “Niraj Kumar; “A Graph-Based Automatic Plagiarism Detection Technique to Handle The Artificial Word Reordering and Paraphrasing”, A. Gelbukh (Ed.): CICLing 2014, LNCS 8404, pp. 481–494, 2014. (LINK)

2. IN TOP SYSTEM @ TAC-2011: My system was in the top system for “Automatic Summarization Evaluation Task” at Text Analysis Conference (TAC 2011), organized by National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2011. (For details, see My Publications)

3. IN TOP SYSTEM @ TAC-2010: My system was in the top system for “Automatic Summarization Evaluation Task” at Text Analysis Conference (TAC 2010), organized by National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2010. (For details, see My Publications).

4. Other Recognition: Our Unsupervised Phrase Identification technique for Keyphrase Extraction, has been appreciated by the survey paper published in COLING-2010, Titled: “Conundrums in Unsupervised Keyphrase Extraction: Making Sense of the State-of-the-Art”

Research Interests

My research interests broadly span in the following areas (including but not limited to):

NLP

1. Conversational AI: Single/Multi-Intent-Slot extraction, Intent-Ordering, Out-Of-Domain Detection, Switching the control from Bot to Human, Dialogue Selection and so on.

2. Code Mixed NLP Applications.

3. Metaverse and NLP

4. Knowledge Representation: Knowledge Graph Construction, Dynamic Ontology, Dynamic Contextual Search System.

5. Emotional-Intelligence & Analytic Features: Emotional Intelligence and NLP based general emotions (like: Weighted Sentiment Analysis, Sarcasm Detection, Emotion “Anger, Fear, Joy/happiness, & Sadness, etc.”, Extraction, Valence, Arousal Dominance Extraction) and so on.

6. NLP (related to Social Media): Hate Speech and Hate Target Classifier, Aggression Identification from Text, Automatic extraction of Threat, Insult, Complain and C

7. NLP General: Keyphrase Extraction, Named Entity Extraction, Entity Normalization, Single & Multi-document Summarization (Extract, Abstract and Guided Summarization), Summarization Evaluation, Text Clustering, Classification, Automatic Question Answering, Automatic Plagiarism Detection.

8. Recommendation System.

Deep Learning & Machine Learning

Graph Algorithms and Non-Euclidean Learning

Time Series Forecasting using Deep Learning 

Other Professional Activities.

1. Program Committee Member: (1) CODS-COMAD – 2018, 2019, 2020, 2021, 2022 (2) ICON 2013, 2016, 2020, 2021, (3) AI-ML Systems - 2022 

2. Reviewed Journal paper: Oxford Journals -> Science & Mathematics -> “Computer Journal”, IEEE ACCESS.

3. Prepared E-Books: video E-Book on Deep Learning, video E-Book on Machine Learning (to be completed)

4. Latest Presentation and seminars: (1) Tech Talk @ SRM University

Academic Qualifications

I obtained my PhD, (CSE) from IIIT-Hyderabad (June-2015), under the guidance of Dr. Kannan Srinathan and Dr. Vasudeva Varma.

PhD Thesis Title: Towards Intelligent Text Mining: Under Limited Linguistic Resources.

Academic Qualification Summary:

1.     PhD (CSE) IIIT-Hyderabad – July-2015

2.     MCA – IGNOU (Delhi) – 2002 Jan - June-2004

3.     BCA – IGNOU (Delhi) –1999-Jan – 2002-June

Publications.

Patents Granted and Filed.

1. Niraj Kumar, Bhiman Kumar Baghel; ( US Patent - US20230402187A1 ); Method and system for mitigating physical risks in an IOT environment; 2023/12/14.

2. Niraj Kumar, Bhiman Kumar Baghel; ( US Patent - 20230077874A1 ), Methods and systems for determining missing slots associated with a voice command for an advanced voice interaction.  Mar 16, 2023.

3. Niraj Kumar, ( US-Patent - US20200410321A1 ); Neural network systems and methods for event parameter determination.

4. Ambrish Gupta, Niraj Kumar; ( US Patent - US20230325604A1 ); Method and system for automated sentiment classification; 2023/10/12.

5. Niraj Kumar, ( US Patent - US20210240938A1 ) Neural network systems and methods for target identification from text. Obtained US Patent.

6. Filed 3 Patents @ Fujitsu Research India.

Refereed journal articles (Published)

1. Niraj Kumar, Bhiman Kumar Baghel, “Intent Focused Semantic Parsing and zero-shot Learning for Out-of-Domain detection in Spoken Language Understanding” has been accepted for publication in IEEE Access. [Dec-2021]

2. Niraj Kumar, Bhiman Kumar Baghel, “Smart Stacking of Deep Learning Models for Granular Joint Intent-Slot Extraction for Multi-Intent SLU” has been accepted for publication in IEEE Access. [June-2021]

3. Niraj Kumar, Kannan Srinathan and Vasudeva Varma; “Unsupervised Deep Semantic and Logical Analysis for Identification of Solution Posts from Community Answers”; “Int. J. of Information and Decision Sciences”,  IJIDS 8(2): 153-178 (2016).

4. Niraj Kumar, Kannan Srinathan and Vasudeva Varma; “A Graph based Unsupervised N-gram Filtration Technique for Automatic Keyphrase Extraction”; “Int. J. of Data Mining, Modelling and Management”, Vol. 8, No. 2: 124-143, (2016)

Peer-reviewed proceedings (Published)

1. Supriya Bajpai, Krishna Murthi, Niraj Kumar, AnomGraphAdv: Enhancing Anomaly and Network Intrusion Detection in Wireless Networks Using Adversarial Training and Temporal Graph Networks. Accepted for publication in ACM WiSec 2024. 

2. Nikhil Cherian Kurian, Niraj Kumar; Improved Multi-Step, Multi-Variate, and Spatiotemporal 5G Data Usage Forecasting Without Deploying Data Imputation Techniques; 2023 IEEE Global Communications Conference.

3. Anant Khandelwal, Niraj Kumar; A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts. COMAD/CODS 2020: 55-64.

4. Niraj Kumar; “A Graph Based Automatic Plagiarism Detection Technique to Handle the Artificial Word Reordering and Paraphrasing” CICLing 2014, LNCS 8404, pp. 481–494, 2014. (My work @ TCS Innovation Lab; best paper award, 1st place @ CICLing 2014).

5. Niraj Kumar and Lipika Dey; “Automatic Quality Assessment of documents with Application to Essay grading”; accepted for publication in MICAI-2013. (My work @ TCS Innovation Lab).

6. Niraj Kumar, Kannan Srinathan, Vasudeva Varma: A Knowledge Induced Graph-Theoretical Model for Extract and Abstract Single Document Summarization. CICLing (2) 2013: LNCS 7817, pp. 408-423.

7. Niraj Kumar, Rashmi Gangadharaiah., Kannan Srinathan and Vasudeva Varma; “Exploring the Role of Logically Related Non-Question Phrases for Answering Why-Questions”; Accepted for publication in NLDB-2013.

8. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  Using Graph Based Mapping of Co-Occurring Words and Closeness Centrality Score for Summarization Evaluation; A. Gelbukh (Ed.): CICLing 2012, LNCS 7182, pp. 353–365, 2012.

9. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  Using Wikipedia Anchor Text and Weighted Clustering Coefficient to Enhance the Traditional Multi-Document Summarization; A. Gelbukh (Ed.): CICLing 2012, LNCS 7182, pp. 390–401, 2012.

10. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma; Using Unsupervised System with least linguistic features for TAC-AESOP Task; In: Proceedings of Text Analysis Conference (TAC 2011), National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC-2011.

11. Niraj Kumar, Kannan Srinathan, and Vasudeva Varma;  An Effective Approach for AESOP and Guided Summarization Task; In: Proceedings of Text Analysis Conference (TAC 2010), National Institute of Standards and Technology (NIST), Gaithersburg, Maryland, USA TAC 2010.

12. Niraj Kumar,  Kannan Srinathan and Vasudeva Varma;  Evaluating Information Coverage in Machine Generated Summary and Variable Length Documents; COMAD 2010.

13. Niraj Kumar, Venkata Vinay Babu Vemula, Kannan Srinathan, Vasudeva Varma:  Exploiting N-gram Importance and Wikipedia based Additional Knowledge for Improvements in GAAC based Document Clustering. KDIR 2010: 182-187.

14. Niraj Kumar,  Kannan Srinathan and Vasudeva Varma;  Key Fact Extraction from Newswire Articles by Exploiting Local features based weighting and Interaction of sentences,(Published in ICON-2010, length 6-pages)

15. Niraj Kumar and Kannan Srinathan; A New Approach for Clustering Variable Length Documents,(Published in IEEE IACC-09).

16. Niraj Kumar, Kannan Srinathan: Automatic keyphrase extraction from scientific documents using N-gram filtration technique. ACM Symposium on Document Engineering 2008: 199-208.